Analysis of non performing assets in public sector banks of India

Chia sẻ: Huỳnh Ngọc Toàn | Ngày: | Loại File: PDF | Số trang:9

Thêm vào BST

Báo xấu

10
lượt xem 2
download

Download Vui lòng tải xuống để xem tài liệu đầy đủ

In this context, this paper tries to depict both the Gross Non Performing Asset and Net Non Performing Asset position of Public Sector Banks in India and attempts to find whether there is any significant difference among them.

Chủ đề:

Bình luận(0) Đăng nhập để gửi bình luận!

Lưu

Nội dung Text: Analysis of non performing assets in public sector banks of India

International Journal of Management (IJM) Volume 8, Issue 1, January – February 2017, pp.21–29, Article ID: IJM_08_01_003 Available online at http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=8&IType=1 Journal Impact Factor (2016): 8.1920 (Calculated by GISI) www.jifactor.com ISSN Print: 0976-6502 and ISSN Online: 0976-6510 © IAEME Publication ANALYSIS OF NON PERFORMING ASSETS IN PUBLIC SECTOR BANKS OF INDIA Payel Roy Research Scholar, Department of Commerce, University of Kalyani, West Bengal, India Dr. Pradip Kumar Samanta Associate Professor, Department of Commerce, University of Kalyani, West Bengal, India ABSTRACT The Banks being the mobiliser of finances of different sectors of economy, are expected to be strong enough to withstand the shocks like inflation, depression etc. and to cushion the other financial Institutions along with industries and common people against financial crisis. The Public Sector Banks having a large stake of the Government in their Capital structure are preferred by the commoners often. In this context, this paper tries to depict both the Gross Non Performing Asset and Net Non Performing Asset position of Public Sector Banks in India and attempts to find whether there is any significant difference among them. This paper also tries to show the impact of GNPA on Net Profit of the selected banks for the last 5 years.. Key words: Gross Non Performing Assets, Net Non Performing Assets, Net Profit, Public Sector Banks Cite this Article: Payel Roy and Dr. Pradip Kumar Samanta, Analysis of Non Performing Assets in Public Sector Banks of India. International Journal of Management, 8(1), 2017, pp. 21–29. http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=8&IType=1 1. INTRODUCTION In a developing country like India, deficiency of capital is a major characteristic which can pose a threat for the survival, growth and development of all the three sectors of the economy and the economic development as a whole. The role of banking industry is to remove such deficiencies by mobilizing savings towards systematic investments. 2. REVIEW OF LITERATURE Ahmad.Z and Dr. Jegadeeshwaran.M. (2013) attempt to study the non performing assets of nationalised banks. The data was collected for a period of five years and analysed by mean, CAGR, ANOVA and ranking banks. The individual banks got ranks as per their performance in management of NPA‟s. It was also tested, whether there is significant difference between nonperforming assets of banks, it was found http://www.iaeme.com/IJM/index.asp 21 editor@iaeme.com
Payel Roy and Dr. Pradip Kumar Samanta that there is significant difference in the level of NPA‟s of nationalised banks which reflect their varied efficiency in the management of nonperforming assets. Parmar.R (2014) attempts to study the trend of Total advances, Net profit, Gross NPA, Net NPA of SBI and ICICI Bank. During last three years total advances and net profit has shown growing trend in both the banks but compare to SBI, NPA in ICICI bank has shown downward trend because of effective NPA management. It also highlights the relationship between Net Profit and Net NPA, while SBI has shown positive relationship between Net Profit and Net NPA, negative relationship has been found in ICICI between Net Profit and Net NPA. Chatterjee.C et al (2012) attempts to focus mainly on the causes and consequences of NPAs, policy directives of RBI, initiatives of Indian Government, scenario of NPAs sector wise and bank group wise and finally the curative measures for NPAs in India. The paper made a comparative study of NPA‟s of public sector banks, private sector banks and foreign sector banks. It also attempted to understand the relationship between NPA’s net profit and advances and the recovery of NPAs through various channels. Dr. Prasanna.P.K (2014) investigates the determinants of nonperforming loans (NPL) in the Indian banking system with the help of panel data modeling. Panel dataset of 31 Indian banks with yearly data that spans the period of 2000 to 2012 totaling 372 firm years has been analysed. It is found that higher growth rate in savings and GDP is associated with lower NPLs in Indian banks. Higher interest and inflation rates contribute positively to rising non performing loans. Gavade-Khompi.S (2013) focuses on the comparative analysis of NPAs within the Scheduled Commercial Banks in India. The NPAs have been analysed for the period of sixteen (16) years i.e. from 1997-2012. The data has been analyzed by statistical tools such as percentages and Compound Annual Growth Rate (CAGR). The trend values have been calculated with the help of 'least square method' of 'time series analysis'. The study observed improvement in the asset quality of SCBs till 2010-2011and categorically noticed sudden change in the asset quality in the year 2011-12. Joseph. A.L, Dr. Prakash.M (2014) studied the trends of NPA in banking industry from 2008 to 2013, the factors that mainly contribute to NPA raising in the banking industry and also provided some suggestions to overcome this burden of NPA. They found that compared to private sector banks, public sector bank is more in the NPA level. The authors have suggested that Credit Appraisal and Monitoring, adherence to documented risk management policy, proper risk architecture, independent credit risk evaluation, centralized data base, credit management information system and credit modeling can help prevent nonperforming assets to a great extent. Credit modeling, in particular can predict impending sickness. Das.S and Dutta.A (2014) tried to analyse, with the help of secondary data from RBI website, net non- performing asset data of 26 public sector banks, by using Annova statistics, and with the help of SPSS software for the period of 6 years, (2008-2013). The main objective of the study is to find out if there are any significant differences in the mean variation of the concerned banks. This paper also focuses on the reason behind the NPA and its impact on banking operations. The study finds out that there is no significant deference between the means of NPA of the banks at five percent level of significance. 3. RELEVANCE OF THE STUDY At one hand the banks provide finance for the different sectors of economy and on the other hand, they stimulate money supply in the economy on the other. So, the banking industry is expected to be strong enough to withstand the shocks like inflation, depression etc. The banks are also expected to cushion the other financial Institutions along with industries and common people against financial crisis. Also, the Public sector banks having a large stake of the Government in their Capital structure are preferred by the commoners often. So, they should be able to manage their resources and liability position very keenly so that the resources are optimally utilized and liabilities are paid off regularly in order to maintain trust of the depositors. Non Performing Assets are like a black spot in the asset side of a Bank’s Position Statement where the unrecoverable amount of assets is shown. The more it is, the more will be the amount of loss for http://www.iaeme.com/IJM/index.asp 22 editor@iaeme.com
Analysis of Non Performing Assets in Public Sector Banks of India the banks in their banking business. So, it is the hour of the need to have an analysis of NPA position of the banks and to find if there is any significant effect of NPAs on their Net Profits. 4. OBJECTIVES This paper attempts to depict both the GNPA and NNPA position of Public sector Banks in India during the last five years and to find whether there is any significant difference among them. This paper also tries to find the impact of GNPA on NP of the selected Banks. 5. RESEARCH METHODOLOGY Secondary data are used for this study and are analysed using MS Excel and SPSS softwares. The financial data were collected from two websites namely, moneycontrol.com and www. financialservices.gov.in. The Public Sector Banks are considered as per the list given by the Department of Finance, Government of India. Twenty four Public Sector Banks are initially arranged as per their Gross and Net NPAs and then a combined rank is given to each bank. The correlation coefficients are calculated among Gross NPAs of different banks to see whether there is any relation among the GNPAs. Then to find if there is any significant effect of GNPA on the Net Profits of the banks individually, GNPAs of the banks are analyzed again using ANOVA, Regression Analysis and t-test. 6. ANALYSIS AND FINDINGS OF THE STUDY The Gross Non Performing Assets and Net Non Performing Assets of Twenty four Public sector banks of India are considered for the last 5 years i.e. from 2011-12 to 2015-16. 6.1. GNPA and NNPA Position of Public Sector Banks The banks are numbered alphabetically in Table 1 and the averages of GNPA and NNPA with respect to last five years of the selected banks are shown graphically in Figure 1. Table 1 Arrangement of Public Sector Banks alphabetically 1 Allahabad Bank 13 Oriental Bank Of Commerce 2 Andhra Bank 14 PNB 3 Bank Of Baroda 15 Punjab & Sind Bank 4 Bank Of India 16 SBI 5 Bank Of Maharashtra 17 State Bank Of Bikaner & Jaipur 6 Canara Bank 18 State Bank Of Mysore 7 Central Bank 19 State Bank of Travancore 8 Corporation Bank 20 Syndicate Bank 9 Dena Bank 21 Uco Bank 10 I D B I Bank Ltd. 22 Union Bank Of India 11 Indian Bank 23 United Bank Of India 12 Indian Overseas Bank 24 Vijaya Bank Average… 80000 60000 40000 20000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Figure 1 Graphical representation of Average GNPA and NNPA of Public sector Banks http://www.iaeme.com/IJM/index.asp 23 editor@iaeme.com
Payel Roy and Dr. Pradip Kumar Samanta Fig. 1 showed that there is a huge gap between the NPAs of SBI and NPAs of other banks. GNPA of SBI is much ahead of other banks including the second highest one that is PNB. But NNPA of SBI is much below which shows that the NPA provisioning is done prudently as compared to other banks. But the NPA position of SBI is not satisfactory in overall basis. State Bank of Travancore, State bank of Mysore and Punjab & Sind Bank and State Bank of Bikaner & Jaipur have less amount of GNPA and matching amount of provisions which renders their GNPA and NNPA ranks to be almost similar. In Table 2, the banks are arranged according to the last 5 years average data of GNPA and NNPA separately and also a combined ranking is done taking average of the two ranks based on GNPA and NNPA respectively. Table 2 Statement showing Average GNPA, Average NNPA, GNPA based Rank, NNPA based Rank and Combined Rank GNPA NNPA Average Average Based Based Combined Name of the Banks GNPA NNPA Rank Rank Rank 1 Allahabad Bank 7801.31 5442.33 14 14 14 2 Andhra Bank 5,938.05 3246.36 10 9 9.5 3 Bank Of Baroda 16221.14 7849.27 21 19 20 4 Bank Of India 19720.04 11706.99 22 22 22 5 Bank Of Maharashtra 4416.47 2725.68 7 7 7 6 Canara Bank 12507.98 8840.57 19 21 20 7 Central Bank 12364.72 7248.43 18 18 18 8 Corporation Bank 5942.03 3817.19 11 12 11.5 9 Dena Bank 3595.7 2310.52 6 6 6 10 I D B I Bank Ltd. 11704.31 6309.9 16 16 16 11 Indian Bank 4895.18 2982.23 8 8 8 12 Indian Overseas Bank 12903.92 8123.73 20 20 20 13 Oriental Bank Of Commerce 7150.06 4802.9 13 13 13 14 PNB 24515.73 14485.36 23 23 23 15 Punjab & Sind Bank 2433.02 1758.29 2 4 3 16 SBI 61473.87 30453.8 24 24 24 17 State Bank Of Bikaner & Jaipur 2610.33 1558.78 4 3 3.5 18 State Bank Of Mysore 2434.82 1397.34 3 1 2 19 State Bank of Travancore 2374.52 1414.37 1 2 1.5 20 Syndicate Bank 6209.37 3577.86 12 10 11 21 Uco Bank 9802.09 5532.77 15 15 15 22 Union Bank Of India 11705.83 6532.68 17 17 17 23 United Bank Of India 5656.43 3580.35 9 11 10 24 Vijaya Bank 2741.51 1821.34 5 5 5 From the ranks given in Table 2, it is evident that there is not much difference in the ranking of the Banks according to GNPA and NNPA respectively. In most of the cases same ranks are given to the banks in both GNPA and NNPA based ranking column. When the combined ranks are taken up it shows that on overall basis, State of Travancore, State bank of Mysore and Punjab & Sind Bank hold the first, second and third positions respectively, while Bank of India, Punjab National Bank and State Bank of India hold the twenty second, twenty third and twenty fourth positions respectively. Since both GNPA and NNPA based ranking are quite similar for the banks and since the paper studies the NPAs only, leaving the provisioning criterion, so GNPA is taken as a measure for further analysis. http://www.iaeme.com/IJM/index.asp 24 editor@iaeme.com
Analysis of Non Performing Assets in Public Sector Banks of India 6.2. Analysis of GNPA using Correlation Coefficient To find whether there is any significant difference among the NPAs of different banks correlation coefficient is calculated to check homogeneity in the data set. It was found that NPAs of most of the banks are highly correlated with the NPAs of other banks. Table 3, which showed this calculation, depicted that the correlation coefficient of State Bank of Travancore with respect to UCO bank is the least, that too above 0.67 while for others, it is more than 90% in most of the cases. It can be concluded here that in general, there is huge influence of change in GNPAs of each bank on one another. Thus it means that the factors affecting NPAs of the banks are similar in nature as provisions for NPAs are not considered. Table 3 Statement showing Correlation among the GNPAs of the selected banks NAME OF THE Allhbd Andhra Can Corp Dena BANKS Bank Bank BOB BOI BOM Bank CB Bank Bank Allahabad Bank 1 0.9959 0.9645 0.9473 0.9281 0.9446 0.9726 0.9732 0.9646 Andhra Bank 1 0.9651 0.9564 0.9542 0.94944 0.9682 0.983 0.9771 Bank Of Baroda 1 0.995 0.9551 0.99681 0.9953 0.9892 0.9888 Bank Of India 1 0.9735 0.99852 0.9825 0.9899 0.9939 Bank Of Maharashtra 1 0.9596 0.9406 0.9829 0.9878 Canara Bank 1 0.9852 0.984 0.9877 Central Bank 1 0.9859 0.9804 Corporation Bank 1 0.9985 Dena Bank 1 IDBI P&S NAME OF THE BANKS Bank IndBank IOB OBOC PNB Bank SBI SBOB&J Allahabad Bank 0.9785 0.9914 0.9631 0.9593 0.9685 0.975 0.9798 0.9758 Andhra Bank 0.9831 0.997 0.9725 0.9664 0.9715 0.9865 0.9638 0.98418 Bank Of Baroda 0.9955 0.9652 0.9942 0.9972 0.9994 0.9123 0.9769 0.904 Bank Of India 0.9916 0.9601 0.9979 0.9984 0.9962 0.9075 0.9513 0.89506 Bank Of Maharashtra 0.9707 0.9552 0.9787 0.9737 0.9638 0.9381 0.8914 0.92308 Canara Bank 0.989 0.9536 0.9946 0.9966 0.9963 0.8931 0.9585 0.88136 Central Bank 0.9933 0.9617 0.9833 0.99 0.9938 0.9167 0.9881 0.91209 Corporation Bank 0.998 0.9799 0.9951 0.995 0.9932 0.952 0.9592 0.94332 Dena Bank 0.9959 0.9775 0.9979 0.9961 0.9933 0.9448 0.9497 0.93402 I D B I Bank Ltd. 1 0.9807 0.9959 0.9967 0.9978 0.9449 0.9738 0.93755 Indian Bank 1 0.976 0.9663 0.972 0.9824 0.9577 0.97835 Indian Overseas Bank 1 0.998 0.9971 0.9324 0.9568 0.92149 Oriental Bank Of Commerce 1 0.9986 0.9203 0.962 0.9099 PNB 1 0.9239 0.9739 0.91528 Punjab & Sind Bank 1 0.9119 0.99896 SBI 1 0.91325 State Bank Of Bikaner & Jaipur 1 http://www.iaeme.com/IJM/index.asp 25 editor@iaeme.com
Payel Roy and Dr. Pradip Kumar Samanta Syn Uco Union Vij NAME OF THE BANKS SBOM SBOT Bank Bank BOI UBI Bank Allahabad Bank 0.9479 0.8692 0.9413 0.9479 0.966 0.9482 0.9097 Andhra Bank 0.9173 0.8515 0.9482 0.9511 0.9751 0.9505 0.909 Bank Of Baroda 0.8862 0.7439 0.994 0.9915 0.9936 0.8623 0.9849 Bank Of India 0.8389 0.6983 0.9956 0.9927 0.995 0.8416 0.9817 Bank Of Maharashtra 0.7774 0.7106 0.9668 0.9486 0.9809 0.8744 0.926 Canara Bank 0.8475 0.6911 0.9949 0.9952 0.9908 0.8279 0.9877 Central Bank 0.9197 0.7952 0.9881 0.9756 0.9884 0.8899 0.9799 Corporation Bank 0.8745 0.7829 0.9884 0.9752 0.9989 0.9085 0.9612 Dena Bank 0.8522 0.7504 0.9893 0.9809 0.9987 0.8889 0.9622 I D B I Bank Ltd. 0.8934 0.7844 0.9901 0.9827 0.9982 0.9016 0.9691 Indian Bank 0.8995 0.8161 0.9454 0.9612 0.9731 0.9279 0.9061 Indian Overseas Bank 0.8549 0.7294 0.991 0.9914 0.9973 0.8684 0.97 Oriental Bank Of Commerce 0.8624 0.7358 0.9972 0.9885 0.9985 0.8673 0.9817 PNB 0.8829 0.7495 0.9938 0.9915 0.9964 0.8719 0.9801 Punjab & Sind Bank 0.8819 0.8707 0.8949 0.8966 0.9371 0.9685 0.8355 SBI 0.9626 0.8302 0.9542 0.9576 0.9598 0.8933 0.9491 State Bank Of Bikaner & Jaipur 0.8953 0.8894 0.8835 0.8854 0.9273 0.9751 0.8242 State Bank Of Mysore 1 0.923 0.8488 0.8475 0.8669 0.9141 0.8391 State Bank of Travancore 1 0.7181 0.6764 0.7602 0.959 0.6717 Syndicate Bank 1 0.9809 0.9942 0.8489 0.991 Uco Bank 1 0.9815 0.8156 0.9719 Union Bank Of India 1 0.8897 0.9724 United Bank Of India 1 0.7925 Vijaya Bank 1 Table 4 was prepared to show the trends of GNPA and NP of the selected banks over the last five years. It is observed that over the years the NP of the banks have reduced while GNPA has increased. Also, a very gloomy picture of the PSBs are shown in this table as out of twenty four banks, twelve banks have incurred losses in the financial year 2015-16 and the others have made profit that too at reduced rates than the last year except State Bank of Travancore which has witnessed an increase in profit. Except Central Bank and United Bank of India, others have experienced losses in the year 2015-16 for the first time during last five years. Table 4 showing trend of GNPA and NP of the selected PSBs BANK NAME: Allahabad BANK NAME: Andhra BANK NAME: Bank of BANK NAME: Bank of Bank Bank Baroda India Year PL GNPA Year PL GNPA Year PL GNPA Year PL GNPA - - 2015- 15,384.5 2015 2015- 5,395.5 40,521.0 2015 6,089.2 49,879.1 16 -743.31 7 -16 539.84 11,443.63 16 4 4 -16 1 3 2014- 2014 2014- 3,398.4 16,261.4 2014 1,708.9 22,193.2 15 620.9 8,357.97 -15 638.44 6,876.54 15 4 5 -15 2 4 2013- 1,172.0 2013 2013- 4,541.0 11,875.9 2013 2,729.2 11,868.6 14 2 8,068.04 -14 435.58 5,857.60 14 8 0 -14 7 0 2012- 1,185.2 2012 1,289.1 2012- 4,480.7 2012 2,749.3 13 1 5,136.99 -13 3 3,714.49 13 2 7,982.58 -13 5 8,765.25 2011- 1,866.7 2011 1,344.6 2011- 5,006.9 2011 2,677.5 12 9 2,058.98 -12 7 1,798.01 12 6 4,464.75 -12 2 5,893.97 http://www.iaeme.com/IJM/index.asp 26 editor@iaeme.com
Analysis of Non Performing Assets in Public Sector Banks of India BANK NAME:Bank of BANK NAME: Canara BANK NAME: Central BANK NAME: Corporation Maharastra Bank Bank Bank Year PL GNPA Year PL GNPA Year PL GNPA Year PL GNPA 2015- 2015- - 2015- - 2015- 16 100.69 10,385.85 16 2,812.82 31,637.83 16 1,117.67 22,720.88 16 -506.48 14,544.25 2014- 2014- 2014- 2014- 15 450.69 6,402.06 15 2,702.62 13,039.96 15 606.45 11,873.06 15 584.26 7,106.68 2013- 2013- 2013- - 2013- 14 385.97 2,859.85 14 2,438.19 7,570.21 14 1,262.84 11,500.01 14 561.72 4,736.79 2012- 2012- 2012- 2012- 13 759.52 1,137.55 13 2,872.10 6,260.16 13 1,014.96 8,456.18 13 1,434.67 2,048.23 2011- 2011- 2011- 2011- 12 430.83 1,297.03 12 3,282.71 4,031.75 12 533.04 7,273.46 12 1,506.04 1,274.21 BANK NAME: Dena BANK NAME: Indian BANK NAME: Indian Bank BANK NAME: IDBI Bank Bank Overseas Bank Year PL GNPA Year PL GNPA Year PL GNPA Year PL GNPA - - 2015- - 8,560.4 2015- 3,664.8 24,875.0 2015- 8,827.0 2015- 2,897.3 30,048.6 16 935.32 9 16 0 7 16 711.38 4 16 3 3 2014- 4,393.0 2014- 12,684.9 2014- 1,005.1 5,670.4 2014- 14,922.4 15 265.48 4 15 873.39 7 15 7 4 15 -454.33 5 2013- 2,616.0 2013- 1,121.4 2013- 1,158.9 4,562.2 2013- 14 551.66 3 14 0 9,960.16 14 5 0 14 601.74 9,020.48 2012- 1,452.4 2012- 1,882.0 2012- 1,581.1 3,565.4 2012- 13 810.38 5 13 8 6,449.98 13 4 7 13 567.23 6,607.96 2011- 2011- 2,031.6 2011- 1,746.9 1,850.7 2011- 1,050.1 12 803.14 956.5 12 1 4,551.37 12 7 7 12 3 3,920.07 BANK NAME: Oriental BANK NAME: Punjab & Bank of Commerce BANK NAME: PNB Sind Bank BANK NAME: SBI Year PL GNPA Year PL GNPA Year PL GNPA Year PL GNPA - 2015- 14,701.7 2015- 3,974.4 55,818.3 2015- 335.9 4,229.0 2015- 98,172.8 16 156.08 8 16 0 3 16 7 5 16 9,950.65 0 2014- 2014- 3,061.5 25,694.8 2014- 121.3 3,082.1 2014- 13,101.5 56,725.3 15 777.5 7,666.22 15 8 6 15 5 9 15 7 4 2013- 1,139.4 2013- 3,342.5 18,880.0 2013- 300.6 2,553.5 2013- 10,891.1 61,605.3 14 1 5,617.86 14 8 6 14 3 2 14 7 5 2012- 1,327.9 2012- 4,747.6 13,465.7 2012- 339.2 1,536.9 2012- 14,104.9 51,189.3 13 5 4,183.96 13 7 9 13 2 0 13 8 9 2011- 1,141.5 2011- 4,884.2 2011- 451.2 2011- 11,707.2 39,676.4 12 6 3,580.49 12 0 8,719.62 12 9 763.44 12 9 6 BANK NAME: State Bank BANK NAME: State Bank BANK NAME: State Bank BANK NAME: Syndicate of Bikaner & Jaipur of Mysore of Travancore Bank Year PL GNPA Year PL GNPA Year PL GNPA Year PL GNPA 2015- 2015- 2015- 2015- - 16 850.6 3,602.76 16 357.85 3,635.56 16 337.73 3,199.96 16 1,643.49 13,832.16 2014- 2014- 2014- 2014- 15 776.87 2,945.14 15 408.8 2,136.42 15 335.53 2,357.05 15 1,522.93 6,442.38 2013- 2013- 2013- 2013- 14 731.69 2,732.78 14 204.16 2,818.87 14 304.34 3,076.94 14 1,711.46 4,611.13 2012- 2012- 2012- 2012- 13 730.24 2,119.49 13 416.1 2,080.63 13 615.04 1,749.88 13 2,004.42 2,978.50 2011- 2011- 2011- 2011- 12 652.03 1,651.47 12 369.15 1,502.62 12 510.46 1,488.75 12 1,313.39 3,182.70 http://www.iaeme.com/IJM/index.asp 27 editor@iaeme.com
Payel Roy and Dr. Pradip Kumar Samanta 6.3. Impact of GNPA on Net Profit To determine the impact of GNPA on NP of the selected Banks, regression analysis has been done using SPSS software, taking GNPA as independent variable and NP as dependent variable. Also fitness of model is tested. The hypothesis is set as- Ho: There is no impact of GNPA on NP of the selected banks. H1: There is a significant impact of GNPA on NP of the selected banks. Hypothesis test is done through comparison of T value with the critical values for the banks individually. Tables 5 shows the result of the analysis which proves that in most of the banks GNPA proves to be a major factor for the change in NP but in opposite direction, they are inversely correlated to each other and GNPA has huge influence over the change in NP. Punjab & Sind Bank, SBI, United Bank of India, Vijaya Bank and Central Bank have very little influence of GNPA on their NPs. Andhra Bank and Bank of Maharashtra have medium level of influence of GNPA as regards to profits. Others banks are having high level of dependency of NP on GNPA. A high correlation in almost all the banks between GNPA and NP suggests that the association between them is strong and the negative value shows that as the GNPA grows the NP falls. For Andhra Bank, Bank Of Maharashtra, Central Bank, Punjab & Sind Bank, SBI, State Bank Of Mysore, State Bank of Travancore, Union Bank Of India, United Bank of India and Vijaya Bank, the significance value is higher than the 0.05 which renders the model unfit for the data considered. T value of the data in absolute terms, relating to all the banks are more than critical values. So in case of all selected banks, null hypothesis is rejected. Thus it can be concluded here that there is an effect of GNPA on NP of the banks concerned which is further proved by high correlation between these two variables for all the banks. Table 5 Statement showing Test of Hypothesis: COR REG F P T MODEL Sl.No. NAME OF THE BANKS COEFF VALUE VALUE VALUE VALUE FIT H0 1 Allahabad Bank -0.973 0.928 52.572 .005b -7.251 Y Rejected 2 Andhra Bank -0.775 0.467 4.499 .124b -2.121 N Rejected 3 Bank Of Baroda -0.981 0.949 75.183 .003b -8.671 Y Rejected 4 Bank Of India -0.969 0.919 46.6 .006b -6.826 Y Rejected 5 Bank Of Maharashtra -0.794 0.507 5.119 .109b -2.263 N Rejected 6 Canara Bank -0.969 0.918 45.736 .007b -6.763 Y Rejected 7 Central Bank -0.672 0.269 2.473 .214b -1.573 N Rejected 8 Corporation Bank -0.973 0.928 52.434 .005b -7.241 Y Rejected 9 Dena Bank -0.99 0.973 146.599 .001b -12.108 Y Rejected 10 I D B I Bank Ltd. -0.98 0.948 73.634 .003b -8.581 Y Rejected 11 Indian Bank -0.959 0.894 34.783 .010b -5.898 Y Rejected 12 Indian Overseas Bank -0.995 0.987 296.089 .000b -17.207 Y Rejected 13 Oriental Bank Of Commerce -0.975 0.934 57.849 .005b -7.606 Y Rejected 14 PNB -0.988 0.968 122.361 .002b -11.062 Y Rejected 15 Punjab & Sind Bank -0.527 0.036 1.151 .362b -1.073 N Rejected 16 SBI -0.65 0.23 2.196 .235b -1.482 N Rejected State Bank Of Bikaner & 34.294 .010b 17 Jaipur 0.959 0.893 5.856 Y Rejected 18 State Bank Of Mysore -0.375 -0.146 0.492 .534b -0.701 N Rejected 19 State Bank of Travancore -0.841 0.61 7.266 .074b -2.695 N Rejected 20 Syndicate Bank -0.95 0.87 27.75 .013b -5.268 Y Rejected 21 Uco Bank -0.93 0.82 19.211 .022b -4.383 Y Rejected 22 Union Bank Of India -0.831 0.587 6.689 .081b -2.586 N Rejected 23 United Bank Of India -0.658 0.245 2.295 .227b -1.515 N Rejected 24 Vijaya Bank -0.688 0.298 2.701 .199b -1.644 N Rejected http://www.iaeme.com/IJM/index.asp 28 editor@iaeme.com
Analysis of Non Performing Assets in Public Sector Banks of India 7. CONCLUSIONS The analysis carried on in this paper about GNPA shows that the overall NPA position of all the banks is deteriorating over the years. Since there is a negative high correlation between GNPA and NP, the profit gradually decreases as the GNPA grows which has become a serious concern right now. In the financial year 2015-16, most of the banks’ profit has reduced considerably. Some of the banks have incurred losses too. The losses due to increase of NPA can’t be avoided only by making provisions against NPA. Provisioning can act as cushion for NPA losses but it can’t be regarded as a solution for growing NPAs in all the selected PSBs. The banks advancing loans should be cautious enough to consider the backgrounds of loan receiver and make the recovery procedure more stringent. Also, the transparency in disclosure norms should be adhered to diligently by the banks so that the investors’ trust can be maintained. 7.1. Limitations of the Study For this study, only Public Sector Banks are considered where overall picture of NPAs of Banking Industry is not depicted. Due to lack of information from reliable sources about three Public sector banks, they had to be left out. Also, in this study GNPA is taken as a base to find NPA position of the banks which ignored prudency of provisioning. Here, only the effect of GNPA on Net profit is analysed, reasons behind such NPAs are not considered. REFERENCES [1] Ahmad.Z and Dr. Jegadeeshwaran.M. (2013), “COMPARATIVE STUDY ON NPA MANAGEMENT OF NATIONALISED BANKS” International Journal of Marketing, Financial Services & Management Research, ISSN 2277- 3622, Vol.2, No. 8, August (2013). [2] Parmar.R (2014), “Non Performing Assets (NPAs): A Comparative Analysis of SBI and ICICI Bank” International Journal for Research in Management and Pharmacy Vol. 3, Issue 3, April 2014 (IJRMP) ISSN: 2320- 0901. [3] Chatterjee.C et al (2012), “MANAGEMENT OF NON PERFORMING ASSETS – A CURRENT SCENARIO” International Journal of Social Science & Interdisciplinary Research Vol.1 Issue 11, November 2012, ISSN 2277 3630. [4] Dr. Prasanna.P.K (2014), “Determinants of Non Performing Loans in Indian Banking system”, 3rd International Conference on Management, Behavioral Sciences and Economics Issues (ICMBSE'2014) Feb. 11-12, 2014 Singapore. [5] Gavade-Khompi.S (2013), “A COMPARATIVE TREND ANALYSIS OF NON-PERFORMING ASSETS OF COMMERCIAL BANKS IN INDIA”, Research Directions, Volume 1 , Issue 5 / Nov 2013, ISSN:-2321-5488. [6] Dr. V. Shanmugasundaram and S. N. Selvaraj, Credit Defaults Cause Non-Performing Assets in Public Sector Banks in India. International Journal of Management (IJM), 6(1), 2014, pp. 71–78 [7] Joseph. A.L, Dr. Prakash.M (2014), “A Study on Analyzing the Trend of NPA Level in Private Sector Banks and Public Sector Banks”, International Journal of Scientific and Research Publications, Volume 4, Issue 7, July 2014 5 ISSN 2250-3153. [8] Das.S and Dutta.A (2014), “A Study on NPA of Public Sector Banks in India”, IOSR Journal of Business and Management (IOSR-JBM) e-ISSN: 2278-487X, p-ISSN: 2319-7668, Volume 16, Issue 11.Ver. I (Nov. 2014), PP 75-83. [9] Ankur Bhushan and Dr. Giriraj Singh Ahirwar. A Comparative Study of NPA in HDFC & OBC Bank. International Journal of Advanced Research in Management (IJM), 7(3), 2016, pp. 10–20. [10] www.moneycontrol.com. [11] www.financialservices.gov.in. http://www.iaeme.com/IJM/index.asp 29 editor@iaeme.com